In the first of two sequential lessons, students create mobile apps that …
In the first of two sequential lessons, students create mobile apps that collect data from an Android device's accelerometer and then store that data to a database. This lesson provides practice with MIT's App Inventor software and culminates with students writing their own apps for measuring acceleration. In the second lesson, students are given an app for an Android device, which measures acceleration. They investigate acceleration by collecting acceleration vs. time data using the accelerometer of a sliding Android device. Then they use the data to create velocity vs. time graphs and approximate the maximum velocity of the device.
Phenomenological approach to superconductivity, with emphasis on superconducting electronics. Electrodynamics of superconductors, …
Phenomenological approach to superconductivity, with emphasis on superconducting electronics. Electrodynamics of superconductors, London's model, and flux quantization. Josephson Junctions and superconducting quantum devices, equivalent circuits, and high-speed superconducting electronics. Quantized circuits for quantum computing. Overview of type II superconductors, critical magnetic fields, pinning, the critical state model, superconducting materials, and microscopic theory of superconductivity. Alternate years.
This course includes materials on AI programming, logic, search, game playing, machine …
This course includes materials on AI programming, logic, search, game playing, machine learning, natural language understanding, and robotics, which will introduce the student to AI methods, tools, and techniques, their application to computational problems, and their contribution to understanding intelligence. The material is introductory; the readings cite many resources outside those assigned in this course, and students are encouraged to explore these resources to pursue topics of interest. Upon successful completion of this course, the student will be able to: Describe the major applications, topics, and research areas of artificial intelligence (AI), including search, machine learning, knowledge representation and inference, natural language processing, vision, and robotics; Apply basic techniques of AI in computational solutions to problems; Discuss the role of AI research areas in growing the understanding of human intelligence; Identify the boundaries of the capabilities of current AI systems. (Computer Science 405)
This free ESL lesson plan on artificial intelligence has been designed for …
This free ESL lesson plan on artificial intelligence has been designed for adults and young adults at an intermediate (B1/B2) to advanced (C1/C2) level and should last around 45 to 60 minutes for one student.
This course introduces students to the basic knowledge representation, problem solving, and …
This course introduces students to the basic knowledge representation, problem solving, and learning methods of artificial intelligence. Upon completion of 6.034, students should be able to develop intelligent systems by assembling solutions to concrete computational problems, understand the role of knowledge representation, problem solving, and learning in intelligent-system engineering, and appreciate the role of problem solving, vision, and language in understanding human intelligence from a computational perspective.
This Google Presentation Slide Deck is an editable "make and take" of …
This Google Presentation Slide Deck is an editable "make and take" of resources on the topic of artificial intelligence in the classroom. Viewers and editors are welcome to use this resource to learn about AI as well as teach others about it.
Explore some of the wonders of modern engineering in this video from …
Explore some of the wonders of modern engineering in this video from the Sciencenter in Ithaca, New York. Hear a diverse selection of engineers explain how things work.
This course provides a challenging introduction to some of the central ideas …
This course provides a challenging introduction to some of the central ideas of theoretical computer science. Beginning in antiquity, the course will progress through finite automata, circuits and decision trees, Turing machines and computability, efficient algorithms and reducibility, the P versus NP problem, NP-completeness, the power of randomness, cryptography and one-way functions, computational learning theory, and quantum computing. It examines the classes of problems that can and cannot be solved by various kinds of machines. It tries to explain the key differences between computational models that affect their power.
Graduate-level introduction to automatic speech recognition. Provides relevant background in acoustic theory …
Graduate-level introduction to automatic speech recognition. Provides relevant background in acoustic theory of speech production, properties of speech sounds, signal representation, acoustic modeling, pattern classification, search algorithms, stochastic modeling techniques (including hidden Markov modeling), and language modeling. Examines approaches of state-of-the-art speech recognition systems. Introduces students to the rapidly developing field of automatic speech recognition. Its content is divided into three parts. Part I deals with background material in the acoustic theory of speech production, acoustic-phonetics, and signal representation. Part II describes algorithmic aspects of speech recognition systems including pattern classification, search algorithms, stochastic modelling, and language modelling techniques. Part III compares and contrasts the various approaches to speech recognition, and describes advanced techniques used for acoustic-phonetic modelling, robust speech recognition, speaker adaptation, processing paralinguistic information, speech understanding, and multimodal processing.
This free ESL lesson plan on automation has been designed for adults …
This free ESL lesson plan on automation has been designed for adults and young adults at an intermediate (B1/B2) to advanced (C1/C2) level and should last around 45 to 60 minutes for one student.
6.270 is a hands-on, learn-by-doing class, in which participants design and build …
6.270 is a hands-on, learn-by-doing class, in which participants design and build a robot that will play in a competition at the end of January. The goal for the students is to design a machine that will be able to navigate its way around the playing surface, recognize other opponents, and manipulate game objects. Unlike the machines in Introduction to Design (2.70), 6.270 robots are totally autonomous, so once a round begins, there is no human intervention. The goal of 6.270 is to teach students about robotic design by giving them the hardware, software, and information they need to design, build, and debug their own robot.
This textbook was written for a community college introductory course in spreadsheets …
This textbook was written for a community college introductory course in spreadsheets utilizing Microsoft Excel. While the figures shown utilize Excel 2016, the textbook was written to be applicable to other versions of Excel as well. The book introduces new users to the basics of spreadsheets and is appropriate for students in any major who have not used Excel before.
Study of an area of current interest in theoretical computer science. Topic …
Study of an area of current interest in theoretical computer science. Topic varies from term to term. This course is a study of Behavior of Algorithms and covers an area of current interest in theoretical computer science. The topics vary from term to term. During this term, we discuss rigorous approaches to explaining the typical performance of algorithms with a focus on the following approaches: smoothed analysis, condition numbers/parametric analysis, and subclassing inputs.
This interdisciplinary course provides a hands-on approach to students in the topics …
This interdisciplinary course provides a hands-on approach to students in the topics of bioinformatics and proteomics. Lectures and labs cover sequence analysis, microarray expression analysis, Bayesian methods, control theory, scale-free networks, and biotechnology applications. Designed for those with a computational and/or engineering background, it will include current real-world examples, actual implementations, and engineering design issues. Where applicable, engineering issues from signal processing, network theory, machine learning, robotics and other domains will be expounded upon.
PDF version of a customizable computer science needs assessment that can be …
PDF version of a customizable computer science needs assessment that can be used to gather data from one or more districts. The live Google Form version can be found here: https://docs.google.com/forms/d/e/1FAIpQLSfdSe7LQLNt5L4LykzgWb0PNwjWfAo7CLs82kUhPSeDGLPj3Q/viewform Please contact CESA 11 if you would like an editable Google Form version.
Blender 3D: Noob to Pro is a product of shared effort by …
Blender 3D: Noob to Pro is a product of shared effort by numerous team members and anonymous editors. Its purpose is to teach people how to create three-dimensional computer graphics using Blender, a free software application. This book is intended to be used in conjunction with other on-line resources that complement it.
Do you or your students want to make 3D movies like Pixar's …
Do you or your students want to make 3D movies like Pixar's Toy Story? This two period to a two-week unit is perfect for students or classrooms that want to learn about the basics of 3D animation using Blender, without the need to invest any money. I use this unit as a two-block period (about 180 minutes total). Some students continue making activities even after the formal lessons are complete.
This used as a unit in Intro to Programming (renamed-- Exploring Computer Science) but would fit well into a game design course as well.
Students learn about the similarities between the human brain and its engineering …
Students learn about the similarities between the human brain and its engineering counterpart, the computer. Since students work with computers routinely, this comparison strengthens their understanding of both how the brain works and how it parallels that of a computer. Students are also introduced to the "stimulus-sensor-coordinator-effector-response" framework for understanding human and robot actions.
Learn through interactive problem solving – proven to be more effective than …
Learn through interactive problem solving – proven to be more effective than lectures. Enjoy interactive explorations written by award-winning teachers, researchers, and professionals. Brilliant guides you through an interactive exploration of concepts and principles, and helps you build your quantitative intuition. Learn frameworks for thinking and solving challenging problems, instead of memorizing formulas.
Students create projects that introduce them to Arduino—a small device that can …
Students create projects that introduce them to Arduino—a small device that can be easily programmed to control and monitor a variety of external devices like LEDs and sensors. First they learn a few simple programming structures and commands to blink LEDs. Then they are given three challenges—to modify an LED blinking rate until it cannot be seen, to replicate a heartbeat pattern and to send Morse code messages. This activity prepares students to create more involved multiple-LED patterns in the Part 2 companion activity.
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